The
Lytro Camera captures a 4D light field of a scene,
enabling photographs to be digitally refocused after images are captured.

Computational
illumination is used within the movie industry to render the performances of
live actors into digital environments.

The
NvidiaTegra Shield is an
Android-based tablet that features a 5-megapixel camera with an easy to use
camera API.

Course Goals

To
teach the fundamentals of modern camera architectures and give students hand-on
experience acquiring, characterizing, and manipulating data captured using a
modern camera platform. For example, students will learn how to estimate scene
depth from a sequence of captured images.

Course Description

This
course is the first in a two-part series that explores the emerging new field
of Computational Photography. Computational
photography combines ideas in computer vision, computer graphics, and image
processing to overcome limitations in image quality such as resolution, dynamic
range, and defocus/motion blur. This course will first cover the fundamentals
of image sensing and modern cameras.We will then continue to explore more advanced topics in computer
vision. We will then use this as a basis to explore recent topics in
computational photography such as motion/defocus deblurring
cameras, light field cameras, and computational illumination.

This
course will consist of six homework assignments and no midterm or final exam. We will provide aNvidiaTegra tablet for
each student in the course. Students will write programs that run on the phone
to capture photos. Enrollment is limited to 15 students.

Prerequisites

EECS 211 and/or 230 or permission from instructor. Students should have
experience with C/C++ and MATLAB programming. If you are interested, please
contact the instructor to discuss!

Coursework and Grading

The
course will consist of 6 homework assignments. Each assignment will consist of
some camera programming and some image processing. The camera programming will
be done in C/C++ and the image processing will be done using MATLAB.

Grading
will be based on a 100 point system. The homeworks will constitute the bulk of the course grade (90
points in total). Class attendance will constitute the other 10 points.
Instructions for completing each assignment can be found at the following links:

A
discussion for each homework assignment has been created on Blackboard. Please
post all of your questions on the discussion board so that others may learn
from your questions as well. Do not email the professor or TA directly with
homework questions.

All Homeworks
are to be submitted via Blackboard by 11:59pm on the due date. Each student
will be permitted ONE late submission for partial credit. Two points shall be
docked from the submission for each 24-hour period. For instance, if the
homework is due Tuesday at 11:59pm and it is submitted Wednesday between 12:00am
and 11:59pm, 2 points will be docked. If the assignment is submitted on
Thursday between 12:00am and 11:59pm, 4 points will be docked, and so on. Only
ONE late assignment per student will be awarded partial credit. Any additional
late assignments will receive no credit.

Course Syllabus

Tuesday
9/23/14

Introduction

Thursday
9/25/14

Image
Formation

Tuesday
9/30/14

Image
Sensing

Thursday
10/2/14

Image
Processing I

Tuesday
10/7/14

Image
Processing II

HW1
Due

Thursday
10/9/14

Edge
Detection

Tuesday
10/14/14

Flash
and Lighting

Thursday
10/16/14

Radiometry

HW2
Due

Tuesday
10/21/14

HDR
Imaging

Thursday
10/23/14

Shape
from Shading

Tuesday
10/28/14

Photometric
Stereo

HW3
Due

Thursday
10/30/14

Structured
Light

Tuesday
11/4/14

Depth
from Defocus

Thursday
11/6/14

SIFT

Tuesday
11/11/14

Camera
Calibration

HW4
Due

Thursday
11/13/14

Stereo

Tuesday
11/18/14

Optical
Flow

Thursday
11/20/14

Light
Fields

HW5
Due

Tuesday
11/25/14

No
Class

Thursday
11/27/14

Thanksgiving

Tuesday
12/2/14

Light
Transport

Thursday
12/4/14

Selected
Topics

HW6
Due

Texts

Computational
photography is a new and exciting field. No standard texts on this topic are
available yet. Reading material and class slides will be will be available
before each class. Optional texts include:

Many of
the course materials are modified from the excellent class notes of similar
courses offered in other schools by Shree Nayar,
Marc Levoy,
JinweiGu, Fredo Durand, and others. The instructor is
extremely thankful to the researchers for making their notes available online.